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From simple filtering to tagging

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Part of the Lecture Notes in Computer Science book series (LNCS, volume 597)

Abstract

In the previous sections, we discussed filtering algorithms for dynamic constraint networks. We started with a simple filtering algorithm for computing local consistency and introduced an extension of filtering to use it as a general constraint satisfaction algorithm. In contrast to a backtracking approach, filtering combined with tagging is a kind of breadth-first method for solving dynCSPs. Although it is more expensive to compute all solutions instead of looking for one tuple that satisfies the constraints, this makes sense, as many dynCPs have a huge search space but only a few solutions.

Keywords

Dynamic Network Dynamic Constraint Constraint Network Simple Filter Local Consistency 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

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